This invention relates to a system for noise suppression, particularly a noise canceler capable of cancelling background noise in a voice signal that is intermingled with noise, an accompanying method and a transceiver.
In many cases, noise corrupts a voice (speech) signal and hence the quality of recognition of the voice signal significantly. An example for such noise is background noise intermingled with the voice signal acquired by a microphone, a hand-free phone, a handset or the like.
It is important to recognize voice in a noisy environment, e.g. a construction site, a sport club, a Karaoke room, a hands-free communication system in a vehicle, especially a car, a helicopter, a tank or the like. Furthermore, noise suppression is useful in a live reporting system, a public addressing system or the like.
The recognition of voice can be done by an automatic voice recognition system or by at least one human listener.
The undesirable background noise can be of different sources. For example, making telephone calls out of a driving car, the driving noise, especially the noise of the engine, is a dynamically varying kind of noise that results in poor recognition of the voice, particularly in a hands-free speaking environment of the car. The addressee permanently hears a contaminated acoustic signal, in which the voice of the driver is included but difficult to understand. As a consequence, the driver has to speak up or take the handset of the telephone, which binds his attention to the handset and not the trafficxe2x80x94a very undesirable effect.
Moreover, there are lots of sites which need better recognition of voice and/or better understanding because of a noisy background. Some sites, additional to the above mentioned scenarios, are: airplanes, helicopters, airports, trains, buses, train stations, bus stops, construction sites, highways, streets or the like.
In [1] a concept and basic approach for adaptive noise cancellation are given. It can be used to eliminate background noise and improve a signal-to-noise-ratio (SNR). Therefore, a main input containing a corrupted signal and a reference input containing noise correlated in some unknown way with the primary noise are used. This reference input is adaptively filtered and subtracted from the main input to obtain the signal estimate. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. Wiener solutions are developed to describe asymptotic adaptive performance and output SNR for stationary stochastic inputs, including single and multiple reference inputs. These solutions show that, when the reference input is free of signal and certain other conditions are met, noise in the main input can be essentially eliminated without signal distortion. In this case, the canceler behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
A kind of adaptive noise canceler with adaptive cross-talk filters can be found in some articles and patents. [1] is used as a basis for improvement to eliminate cross-talk between voice and noise signals from a main input and a reference input (see [2], [3] and [4] for further details).
In [5] a different configuration of a cross-talk adaptive noise canceler is developed by splitting the adaptive cross-talk filter into a pre-filter section and an adaptive filter section.
Document [6] discloses a noise canceler utilizing four adaptive filters and a signal-to-noise power ratio estimator to do cross-talk noise cancellation. Furthermore, adjustment of the step sizes of the two main adaptive cross-talk filters is provided to incorporate a better tracking ability while the wanted voice signal does not exist. On the other hand, a smaller residual noise is achieved while the wanted voice signal is present.
FIG. 1 shows a noise canceler as disclosed in [6]. This noise canceler includes a main input 1 (first microphone) to obtain a main signal x1(n), a reference input 2 (second microphone) to obtain a reference signal x2(n), a signal output 5, adaptive filters 3 and 6, adders 4 and 7, delay circuits 8 and 9, a signal-to-noise power ratio estimator 10 and a step size output circuit 11. The signal-to-noise power ratio estimator 10 is made up of adaptive filters 12 and 13, adders 14 and 15, power mean circuits 16, 17, 18 and 19, and Dividers 20 and 21.
The main signal x1(n) is delayed by the delay circuit 8 by D samples to turn out a delayed main signal. This delayed main signal is applied to the subtracter 4. On the other hand, the reference signal x2(n) is delayed by the delay circuit 9 by D samples to turn out a delayed reference signal that is applied to the subtracter 7. The adaptive filter 3 operates to estimate a noise signal included in the main signal x1(n) while the adaptive filter 6 operates to estimate a desired signal included in the reference signal x2(n). To allow the filter 3 to estimate the noise signal y1(n), the desired signal y2(n) estimated by filter 6 is subtracted from the reference signal x2(n) by the subtracter 7, and the resulting noise signal e2(n) is input to the filter 3. Likewise, the noise signal y1(n) estimated by the filter 3 is subtracted from the main signal x1(n), and the resulting desired signal e1(n) is input to filter 6. For this purpose, the two filters 3 and 6 are cross-coupled, as illustrated.
Now, for the adaptive filter 3 to estimate the noise signal y1(n) in the main signal accurately, it is necessary to increase the amount of updating of the filter coefficient when the desired signal of the main signal obstructing the estimation is smaller than the noise signal to be estimated. Conversely, when the desired signal of the main signal is greater than the noise signal, it is necessary to reduce the above amount because the signal obstructing the estimation is greater than the noise signal.
On the other hand, for the adaptive filter 6 to estimate the desired signal of the reference signal accurately, it is necessary to increase the amount of updating of the filter coefficient when the noise signal contained in the reference signal obstructing the estimation is smaller than the desired signal. Conversely, when the noise signal of the reference signal is greater than the desired signal, it is necessary to reduce the above amount because the signal obstructing the estimation is greater than the desired signal.
The coefficient for each adaptive filter can be controlled to meet the above requirement by controlling the step size of the adaptive filters.
It is a significant disadvantage of the system disclosed in [6] that the noise canceler as shown in FIG. 1 comprises a signal-to-noise power ratio estimator 10 with two additional adaptive filters 12 and 13. The computations of the noise canceler are increased due to these filters 12 and 13. Moreover, the adaptive filters 12 and 13 embody fixed step sizes affecting an inflexible voice and noise estimation.
It is an object of the present invention to provide an acoustic noise canceler to be able to achieve a good noise cancellation with reduced computational effort.
Furthermore, it is an object of the invention to provide a noise suppression system and an accompanying method.
More specifically, it is an object of the invention to provide an adaptive cross-talk noise canceler which comprises two cross-coupled adaptive filters with adjustable step sizes for updating the coefficients of the filters.
Other objects, features and advantages according to the present invention will be presented in the following detailed description of the illustrated embodiments when read in conjunction with the accompanying drawings.
These objects of the present invention are achieved by the features of the independent claims. Additional features result from the dependent claims.
A noise canceler of the present invention is composed of a main signal input, a reference signal input, a signal output, a voice detection circuitry, a step decision circuitry and two adaptive filters.
The main input receives a main signal which is a voice signal (speech signal) contaminated by noise. The reference input receives a reference signal which is a noise intermingled by cross-talk voice signal (speech signal). The signal output sends out the voice signal with suppressed noise. Further processing might be provided as an automatic voice recognition system. Alternatively, the human listener is the recipient of the noise suppressed voice signal.
The Voice Detection Circuitry detects whether or not voice signal is present. A measurement regarding to the voice signal is obtained based on a certain criterion (either power mean or cross-correlation). The presence of voice can be measured as a comparison of the value of that measurement with a predefined threshold value. Then the comparison results are used to determine the presence of the voice signal. The mechanism about the measurement and comparison will be described in detail latter.
The Step Size Decision Circuitry decides about the size of the steps that should be used for the next update of the two adaptive filters. The first adaptive filter 3 estimates the noise which is used to cancel the noise contained in the main signal. The second adaptive filter 6 estimates the voice signal which is used to remove the voice signal contained in the reference signal.
It is another embodiment of the present invention that the described system is a transceiver.
It is yet another embodiment of the present invention to provide a method for noise suppression to be executed on any of the above described systems.